Bibliographic record
Abstract
During the immediate postwar period, transit infrastructure underwent a vast expansion in the Toronto area. Tens of kilometres of new subway lines were built and commuter rail was introduced across one of the fastest-growing urban regions in Canada. This period was also characterized by a top-down approach to planning, with limited community consultation. Today, community consultation is formally embedded in the transit planning process, but is often the source of tension and mistrust. This paper describes what has changed since the 1960s. Using case studies of the Bloor-Danforth Subway (1966), the Davenport Diamond Project (2015– ), and the Hurontario Light Rail Transit Project (2010– ), the paper explores how planning in the immediate postwar period reflected a top-down, hierarchical structure that did not offer opportunities for meaningful community consultation and in which access, equity, and community-building were not priorities. In contrast, much contemporary planning has been characterized by the inability to satisfy an increased desire for public input in a meaningful way. The result is distrust between the public and planners.This paper suggests that community consultation should be integrated into the earliest stages of the planning process to ensure that such plans proceed into the expensive construction process, with its numerous contracted-out labour and technical aspects, with much broader support.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.026 | 0.031 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".